In this work, an interactive optimisation framework—a combination of a low fidelity flow
solver, Athena Vortex Lattice (AVL), and an interactive Multi-Objective Particle Swarm Optimisation
(MOPSO)—is proposed for aerodynamic shape design optimisation of any aerial vehicle platform.
This paper demonstrates the benefits of interactive optimisation—reduction of computational time
with high optimality levels. Progress towards the most preferred solutions is made by having the
Decision Maker (DM) periodically provide preference information once the MOPSO iterations are
underway. By involving the DM within the optimisation process, the search is directed to the region
of interest, which accelerates the process. The flexibility and eciency of undertaking optimisation
interactively have been demonstrated by comparing the interactive results with the non-interactive
results of an optimum design case obtained using Multi-Objective Tabu Search (MOTS) for the Aegis
UAV. The obtained results show the superiority of using an interactive approach for the aerodynamic
shape design, compared to posteriori approaches. By carrying out the optimisation using interactive
MOPSO it was shown to be possible to obtain similar results to non-interactive MOTS with only
half the evaluations. Moreover, much of the usual complexity of post-data-analysis with posteriori
approaches is avoided, since the DM is involved in the search process
